We are looking for an experienced AI Cloud Data Architect to design, implement, and govern enterprise-scale data and AI platforms on cloud environments. The ideal candidate will have strong expertise in cloud-native data architectures, AI/ML platforms, data governance, and modern analytics ecosystems. This role will drive the design of scalable, secure, and resilient solutions that enable advanced analytics, Generative AI, and machine learning use cases.
Experience: 8–12+ years overall, with at least 4–5 of those in cloud data architecture (not just engineering) and a minimum of 2–3 years working with GenAI/LLMs/RAG in a real delivery context — not just personal projects. Candidates with experience in agentic AI — multi-agent orchestration, AI agent design, or agentic platform delivery — are strongly preferred. At least one regulated industry engagement at architect level is required. Total years matter less than the right combination of data architecture seniority and genuine GenAI/agentic AI depth.
Industry: Banking or Financial Services strongly preferred. Regulated industries (insurance, public sector, telco) acceptable.
Cloud: Azure-native candidates first. AWS or GCP experience is fine as a secondary, but they must know Azure well — the client stack is Azure-centric.
Data Architecture is not enough on its own: A pure data warehouse, BI, or ETL architect won't fit. Look for candidates who have crossed into GenAI territory — RAG, LLMs, vector databases, AI agents. This is non-negotiable for the role.
The governance angle is critical: This is a data governance intelligence platform, not a data platform build. Prioritise candidates who have worked on metadata management, data lineage, compliance frameworks, or audit infrastructure — not just pipeline engineering.
Agentic AI experience is a differentiator: Candidates who have worked with agent orchestration, MCP (Model Context Protocol), human-in-the-loop workflows, or guardrail/observability design for AI systems will stand out strongly.
Core tech to look for: Azure Databricks, Azure Data Factory, Azure OpenAI, Entra ID, RAG/LLM, Python/PySpark, OTEL or audit logging, CI/CD.
Certifications worth flagging: Azure Solutions Architect Expert, Azure AI Engineer Associate, Databricks certifications — any of these are a positive signal.
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Data Architect in Paris employeur : Avensys Consulting
En tant qu'employeur, notre entreprise se distingue par son engagement envers le développement professionnel et la culture collaborative. Située à Paris, nous offrons un environnement de travail dynamique où les consultants peuvent s'épanouir grâce à des projets stimulants et des opportunités de croissance continue. Nos employés bénéficient d'une flexibilité de travail, d'un accès à des outils de pointe et d'une forte orientation vers l'innovation, ce qui en fait un lieu idéal pour ceux qui cherchent à faire une différence significative dans le domaine du conseil.
